• DocumentCode
    620588
  • Title

    A survey of intelligent network fault diagnosis technology

  • Author

    Lv Feng ; Li Xiang ; Wang Xiu-qing

  • Author_Institution
    Coll. of Phys. Sci. & Inf. Eng., Hebei Normal Univ., Shijiazhuang, China
  • fYear
    2013
  • fDate
    25-27 May 2013
  • Firstpage
    4874
  • Lastpage
    4879
  • Abstract
    This paper firstly discusses the common fault types of networks, and the necessity and importance of intelligent fault diagnosis for networks. Secondly, the basic process for network diagnosis systems is put forward. Thirdly, the basic idea and various popular methods of network fault diagnosis based on the intelligent technology, such as: Expert System, Bayesian Network, Rough Set and Neural Networks, are reviewed. Finally, the existing problems and the future research direction for network fault diagnosis are discussed.
  • Keywords
    artificial intelligence; computer network reliability; fault diagnosis; fault tolerant computing; Bayesian network; expert system; intelligent network fault diagnosis technology; network diagnosis systems; neural networks; rough set; Computers; Data models; Educational institutions; Fault diagnosis; Neural networks; Support vector machines; Training; Data Mining; Machine Learning; Network Fault Diagnosis; Pattern Recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2013 25th Chinese
  • Conference_Location
    Guiyang
  • Print_ISBN
    978-1-4673-5533-9
  • Type

    conf

  • DOI
    10.1109/CCDC.2013.6561817
  • Filename
    6561817